Title :
Development of a distributed IMM algorithm for multi-platform multi-sensor tracking
Author :
Ding, Zhen ; Hong, Lang
Author_Institution :
Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA
Abstract :
In this paper, a distributed interacting multiple model (DIMM) algorithm for multi-platform multi-sensor tracking is presented, where the overall target model space is decomposed into all platforms. Each platform contains only a model subset, and interacting multiple model filtering is performed on all platforms. By exchanging some moderate filtering results through a platform communication datalink, a distributed interacting multiple model algorithm can be obtained. Since the DIMM has the advantages of distributed models and distributed measurements as well, significant computation can be saved and good performance can be achieved
Keywords :
Monte Carlo methods; filtering theory; sensor fusion; tracking; communication datalink; distributed interacting multiple model algorithm; interacting multiple model filtering; multi-platform multi-sensor tracking; Bandwidth; Bayesian methods; Distributed computing; Filter bank; Filtering algorithms; Merging; Missiles; Sensor fusion; State estimation; Target tracking;
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 1996. IEEE/SICE/RSJ International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-3700-X
DOI :
10.1109/MFI.1996.572217